Source code for GPy.plotting.matplot_dep.mapping_plots

# Copyright (c) 2012, GPy authors (see AUTHORS.txt).
# Licensed under the BSD 3-clause license (see LICENSE.txt)

import numpy as np
    from GPy.plotting import Tango
    from matplotlib import pyplot as pb

[docs]def plot_mapping(self, plot_limits=None, which_data='all', which_parts='all', resolution=None, levels=20, samples=0, fignum=None, ax=None, fixed_inputs=[], linecol=Tango.colorsHex['darkBlue']): """ Plots the mapping associated with the model. - In one dimension, the function is plotted. - In two dimsensions, a contour-plot shows the function - In higher dimensions, we've not implemented this yet !TODO! Can plot only part of the data and part of the posterior functions using which_data and which_functions :param plot_limits: The limits of the plot. If 1D [xmin,xmax], if 2D [[xmin,ymin],[xmax,ymax]]. Defaluts to data limits :type plot_limits: np.array :param which_data: which if the training data to plot (default all) :type which_data: 'all' or a slice object to slice self.X, self.Y :param which_parts: which of the kernel functions to plot (additively) :type which_parts: 'all', or list of bools :param resolution: the number of intervals to sample the GP on. Defaults to 200 in 1D and 50 (a 50x50 grid) in 2D :type resolution: int :param levels: number of levels to plot in a contour plot. :type levels: int :param samples: the number of a posteriori samples to plot :type samples: int :param fignum: figure to plot on. :type fignum: figure number :param ax: axes to plot on. :type ax: axes handle :param fixed_inputs: a list of tuple [(i,v), (i,v)...], specifying that input index i should be set to value v. :type fixed_inputs: a list of tuples :param linecol: color of line to plot. :type linecol: :param levels: for 2D plotting, the number of contour levels to use is ax is None, create a new figure """ # TODO include samples if which_data == 'all': which_data = slice(None) if ax is None: fig = pb.figure(num=fignum) ax = fig.add_subplot(111) plotdims = self.input_dim - len(fixed_inputs) from ..gpy_plot.plot_util import x_frame1D, x_frame2D if plotdims == 1: Xu = self.X * self._Xscale + self._Xoffset # NOTE self.X are the normalized values now fixed_dims = np.array([i for i,v in fixed_inputs]) freedim = np.setdiff1d(np.arange(self.input_dim),fixed_dims) Xnew, xmin, xmax = x_frame1D(Xu[:,freedim], plot_limits=plot_limits) Xgrid = np.empty((Xnew.shape[0],self.input_dim)) Xgrid[:,freedim] = Xnew for i,v in fixed_inputs: Xgrid[:,i] = v f = self.predict(Xgrid, which_parts=which_parts) for d in range(y.shape[1]): ax.plot(Xnew, f[:, d], edgecol=linecol) elif self.X.shape[1] == 2: resolution = resolution or 50 Xnew, _, _, xmin, xmax = x_frame2D(self.X, plot_limits, resolution) x, y = np.linspace(xmin[0], xmax[0], resolution), np.linspace(xmin[1], xmax[1], resolution) f = self.predict(Xnew, which_parts=which_parts) m = m.reshape(resolution, resolution).T ax.contour(x, y, f, levels, vmin=m.min(), vmax=m.max(), # @UndefinedVariable ax.set_xlim(xmin[0], xmax[0]) ax.set_ylim(xmin[1], xmax[1]) else: raise NotImplementedError("Cannot define a frame with more than two input dimensions")